Paddy Hobson

We are working with a fast-scaling robotics company developing next-generation “Physical AI” systems - combining real-time control, human-in-the-loop teleoperation, and intelligent robotics to enable high-quality data generation and robot learning in the real world. This is a senior, hands-on engineering role focused on building and scaling teleoperation systems that directly control real robots in complex, real-world environments. The Role You will design and implement high-performance robotics software for teleoperation and telepresence systems, enabling intuitive and reliable human control of robotic platforms. The core challenge is making robot motion feel natural, stable, and physically consistent - requiring strong engineering across control systems, kinematics, and real-time robotics software architecture. You’ll work closely with robotics, hardware, and research teams to build systems that are not just functional in simulation, but robust under real-world physical constraints. Key ResponsibilitiesArchitect and develop teleoperation and telepresence software for robotic systemsBuild scalable robotics software infrastructure for real-time robot control and deploymentDesign and implement control systems for smooth, stable human-in-the-loop robot operationDevelop simulation and testing environments to validate robot behaviour before deploymentOptimise robotics algorithms for latency, stability, and real-world performanceDefine engineering best practices across robotics software developmentCollaborate with hardware and research teams to align system behaviour with physical constraintsContribute to system design decisions across motion control, kinematics, and data collection pipelinesMentor engineers and support technical decision-making within the teamRequirementsStrong professional experience in robotics software engineering (5 years preferred)Excellent C development skills in production robotics systemsSolid applied understanding of robot kinematics, dynamics, and control theoryStrong experience with ROS / ROS2 and robotics middlewareExperience building real-time or embedded robotics systemsAbility to design and debug complex systems involving hardware software integrationStrong software engineering fundamentals (architecture, testing, performance optimisation)Comfortable working hands-on with robots in real-world environmentsNice to HaveExperience with teleoperation, HRI, or human-in-the-loop robotics systemsBackground in simulation environments (Gazebo, Isaac Sim, CoppeliaSim, etc.)Experience with state machines, behaviour design, or autonomy stacksExposure to sensor fusion or perception systemsExperience working in early-stage or fast-moving robotics teamsThe EnvironmentHigh-ownership engineering culture with strong technical autonomyFocus on real-world robotics over purely simulated or theoretical workFast-moving, product-driven environment with strong hardware integrationEngineers are expected to shape both architecture and implementationOn-site collaboration with robots and physical systems required

Location: Switzerland (Zug / Zurich region) Scope: Pan-European (DACH, France, Italy, Benelux) Type: Full-time | Equity participation | Board-level appointment Search status: Retained & exclusive mandate Overview We are supporting the formation of a new Switzerland-based robotics venture focused on the deployment and integration of advanced robotics solutions into industrial manufacturing and logistics environments across Europe. The business is backed by a well-established industrial investment group with significant existing exposure to manufacturing and automation-heavy operations. The initial phase will focus on identifying, piloting, and scaling practical robotics applications within real production environments, with a strong emphasis on measurable operational impact. This is a founding CEO appointment with full responsibility for building the organisation from the ground up. The Opportunity The CEO will define and execute the strategy to establish a leading European robotics deployment and integration platform, combining advanced AI-enabled robotics technologies with real industrial use cases. The role requires a balance of commercial leadership, operational execution, and deep credibility within industrial automation environments. This is not a research or pure technology leadership role. The focus is on real-world deployment, customer adoption, systems integration, and building a scalable commercial organisation. Key ResponsibilitiesDefine and execute the go-to-market strategy for robotics deployment across European industrial sectorsBuild and lead the organisation across commercial, technical, and operational functionsEstablish strategic partnerships with robotics technology providers and industrial ecosystem partnersDevelop and scale customer relationships across manufacturing, logistics, and production environmentsLead pilot programmes and transition successful use cases into repeatable commercial offeringsDrive fundraising, investor engagement, and long-term strategic planningRepresent the business at senior industry and customer level across EuropeBuild a high-performance leadership team and organisational structureCandidate Profile Essential Experience15–25 years’ experience in industrial automation, robotics, or capital equipment sectorsSignificant P&L or business unit leadership experience (regional, divisional, or equivalent)Proven track record delivering complex automation or robotics solutions into industrial customersStrong commercial background with responsibility for revenue, key accounts, or large-scale deploymentsExperience operating across European markets (particularly DACH, France, Italy, Benelux)Prior exposure to industrial robotics, automation systems, or systems integration environmentsHighly DesirableBackground with established robotics or automation organisations or integratorsExperience scaling industrial technology businesses or building new business unitsFamiliarity with AI-enabled automation, collaborative robotics, or advanced manufacturing systemsStrong network within industrial manufacturing, logistics, or production environmentsPrevious entrepreneurial or venture-backed experiencePersonal AttributesStrong builder mentality with hands-on leadership approachHigh credibility with industrial and manufacturing stakeholdersComfortable operating in a fast-moving, early-stage environmentStrong commercial instinct and execution focusAble to bridge industrial requirements with emerging robotics technologiesWillingness to be based in Switzerland with regular European travelPackage Competitive base salary aligned with senior Swiss industrial leadership benchmarks, combined with a significant equity participation package reflecting founding executive status. Performance-linked incentives tied to commercial milestones, deployments, and company growth. Process & Timeline This is a retained and exclusive search mandate.Longlisting and confidential outreach: underwayInterview process with investors/founders: Starting from 25th MayTarget appointment: Q4 2026All enquiries will be treated in strict confidence.

We are working with a well-funded deep-tech robotics team building next-generation systems that bridge vision, language, and action in the physical world. The focus is on deploying learning-based models directly onto real robotic hardware, moving beyond simulation-heavy research into production-grade embodied AI. This is a hands-on engineering role for someone who has built and deployed learning systems that interact with the real world - not just trained models in isolation. What you’ll be working onBuilding and deploying Vision-Language-Action (VLA) and robotics foundation models on real robotic platformsDeveloping end-to-end learning pipelines from data collection → training → evaluation → real-world deploymentWorking directly with robotic hardware (manipulation systems / mobile robots depending on project scope)Designing large-scale data pipelines from multimodal robot sensor streams (vision, depth, proprioception, action logs)Running structured experimentation across architectures, datasets, and training strategies for physical AI systemsImproving Sim2Real transfer and closing the gap between model performance in simulation and real-world environmentsOptimising inference and latency for real-time robotic control loopsWhat we’re looking for3 years experience in ML/robotics/computer vision with at least some exposure to real-world robotic systemsHands-on experience with VLA, robotics policy learning, RL, imitation learning, or multimodal transformer modelsExperience working across the robotics stack (e.g. ROS, simulation tools such as Isaac / Gazebo / MuJoCo, sensor integration)Strong track record of data-driven experimentation (not purely intuition-led iteration)Experience building or owning data pipelines for ML systems (collection, filtering, labelling, evaluation)Comfortable working close to hardware and debugging real-world system behaviourStrong Python and deep learning framework experience (PyTorch preferred)Nice to haveExperience deploying models directly onto robots (arms, mobile robots, drones, or similar)Exposure to large-scale training (multi-GPU / distributed training)Experience with Sim2Real transfer or domain randomisationBackground in transformer-based robotics policies or foundation modelsExperience with real-time systems or embedded deployment constraintsWhy this role is interestingYou’ll work directly on embodied AI systems operating in the real world, not just simulation researchHigh autonomy across model design, data strategy, and deploymentOpportunity to shape core robotics intelligence systems from the ground upStrong focus on shipping systems that work outside the labLocation / setup Flexible within Europe. Primarily remote working.

We’re working with a well-funded deep-tech company building next-generation AI sensing systems for deployment in complex real-world environments. They’re looking for a Machine Learning Engineer / Applied ML Scientist to help develop and deploy advanced ML models for real-time inference on edge devices. The company operates at the intersection of AI, sensing, embedded systems, and intelligent autonomy, with applications spanning industrial, robotics, environmental, and next-generation sensor platforms. This is a highly technical role suited to someone who enjoys taking ideas from research through to deployment in production systems. The Role You’ll work across the full ML lifecycle - from data processing and model development through to optimisation and deployment on constrained hardware. Typical projects may include:Developing deep learning models for real-world sensor dataBuilding low-latency inference pipelines for edge devicesOptimising models for deployment (quantisation, pruning, compression, distillation)Designing ML systems for noisy or dynamic environmentsWorking closely with hardware, embedded, and systems engineersPrototyping and evaluating new ML architectures and approachesContributing to production ML infrastructure and deployment workflowsWhat They’re Looking ForStrong experience with Python and modern ML frameworks (PyTorch and/or TensorFlow)Experience developing and deploying ML models in production environmentsBackground in one or more of:Edge AIEmbedded MLReal-time inferenceAudio / signal processingSensor fusionComputer visionTime-series modellingUnderstanding of performance optimisation for constrained systemsFamiliarity with Docker, Linux, cloud infrastructure, or MLOps toolingStrong mathematical and problem-solving skillsNice to HaveExperience with on-device AI or ultra-low-power inferenceBackground in robotics, autonomous systems, defence, healthcare, or industrial AIKnowledge of quantisation / pruning / TinyML techniquesExposure to C , embedded systems, or hardware-aware ML optimisationResearch background (PhD/MSc) in ML, signal processing, robotics, physics, or related fieldsWhy Join?Work on genuinely cutting-edge AI systems with real-world deploymentSmall, highly technical engineering teamSignificant ownership and influence over technical directionStrong funding and long-term product visionOpportunity to work closely with leadership on next-generation AI productsLocation: Munich - Onsite Compensation: Highly competitive equity potential depending on experience

We’re working with a venture-backed deep-tech company building next-generation distributed sensing systems designed for deployment in challenging real-world environments.They are hiring a Senior Electronics Engineer to help architect and develop ultra-low-noise, low-power hardware platforms operating under extreme performance and deployment constraints.This is a highly technical, hands-on role within a small engineering team composed largely of top-tier semiconductor, sensing, RF, and embedded systems backgrounds.What You’ll Work OnDesign and optimization of precision analog and mixed-signal electronicsLow-noise sensing front-ends and signal conditioning chainsEMI/EMC-aware PCB architecture and layoutHardware bring-up, debugging, characterization, and validationSystem-level integration across electronics, RF, embedded, and mechanical domainsPerformance optimization for power, robustness, and signal integrityTransition of advanced hardware from prototype through productionThe work combines deep electronics engineering with real-world deployment challenges, requiring careful balancing of:signal quality,power consumption,physical constraints,manufacturability,and environmental robustness.Ideal BackgroundWe are particularly interested in engineers from:advanced sensing systems,semiconductor / mixed-signal environments,RF or instrumentation companies,high-performance embedded hardware teams,or technically elite product engineering organizations.Relevant backgrounds may include:analog/mixed-signal electronics,sensor hardware,RF hardware,precision instrumentation,EMC/signal integrity,low-power systems,or embedded sensing platforms.RequirementsStrong experience in analog and mixed-signal electronics designExperience with low-noise hardware and signal integrity considerationsHands-on PCB development and hardware debugging experienceFamiliarity with lab equipment such as oscilloscopes, VNAs, analyzers, etc.Understanding of EMI/EMC-aware design principlesExperience validating and optimizing real hardware systemsStrong engineering fundamentals and systems thinkingNice to HaveExperience with sensing systems or distributed hardware platformsExposure to production hardware and DFM/DFTBackground in RF, instrumentation, MEMS, or embedded sensingExperience in highly constrained hardware environmentsStartup or advanced R&D experienceWhy This Role Is InterestingThis is not a narrow subsystem role inside a large organization.Engineers here work across architecture, validation, optimization, integration, and production hardware, with unusually broad ownership and direct technical influence on the product direction.The environment is deeply engineering-led, highly selective, and focused on solving difficult real-world hardware problems.Competitive compensation, bonus structure, and meaningful equity included.

Senior ML Engineer – Autonomous Driving (Mapless, AI-First) A well-funded European deep-tech company is building fully AI-driven, mapless autonomous driving technology in collaboration with leading OEMs and Tier 1 suppliers. We are hiring experienced ML engineers who want to move beyond incremental ADAS and work on large-scale, AI-native autonomy systems deployed directly on vehicles. What You’ll Work OnLearning-based scene understanding from raw multimodal sensor dataOnline road topology & lane connectivity extractionMultimodal transformers / graph neural networks for dynamic traffic modelingEnd-to-end perception → prediction → planning architecturesEnsuring geometric & temporal consistency in real-world drivingDeployment of production-grade ML models to embedded vehicle systemsThis is not simulation-only research. Models are trained at scale and validated directly on real vehicles. What We’re Looking ForStrong ML fundamentals (deep learning, transformers, large-scale training)Solid Python skills; C for production integrationExperience in one or more of:Autonomous drivingRobotics3D computer visionMultimodal learningSensor fusionLearning-based planningPhD is welcome but not required. Real-world deployment experience is highly valued. Why Join?Flat technical structure with real ownershipStrong compute infrastructureClose collaboration with major automotive partnersEquity / stock optionsOpportunity to shape next-generation autonomy from the ground upLocation: Germany (hybrid model available)